quantwave_core/indicators/
high_pass.rs

1use crate::indicators::metadata::{IndicatorMetadata, ParamDef};
2use crate::traits::Next;
3use std::f64::consts::PI;
4
5/// HighPass Filter
6///
7/// Based on John Ehlers' "The Ultimate Smoother"
8/// A second-order High Pass filter that rejects low-frequency components
9/// and passes high-frequency components unattenuated.
10#[derive(Debug, Clone)]
11pub struct HighPass {
12    c1: f64,
13    c2: f64,
14    c3: f64,
15    price_history: [f64; 2],
16    hp_history: [f64; 2],
17    count: usize,
18}
19
20impl HighPass {
21    pub fn new(period: usize) -> Self {
22        let period_f = period as f64;
23        let a1 = (-1.414 * PI / period_f).exp();
24        let c2 = 2.0 * a1 * (1.414 * PI / period_f).cos();
25        let c3 = -a1 * a1;
26        let c1 = (1.0 + c2 - c3) / 4.0;
27        Self {
28            c1,
29            c2,
30            c3,
31            price_history: [0.0; 2],
32            hp_history: [0.0; 2],
33            count: 0,
34        }
35    }
36}
37
38impl Next<f64> for HighPass {
39    type Output = f64;
40
41    fn next(&mut self, input: f64) -> Self::Output {
42        self.count += 1;
43        let res = if self.count < 4 {
44            0.0
45        } else {
46            self.c1 * (input - 2.0 * self.price_history[0] + self.price_history[1])
47                + self.c2 * self.hp_history[0]
48                + self.c3 * self.hp_history[1]
49        };
50
51        self.hp_history[1] = self.hp_history[0];
52        self.hp_history[0] = res;
53        self.price_history[1] = self.price_history[0];
54        self.price_history[0] = input;
55        res
56    }
57}
58
59pub const HIGH_PASS_METADATA: IndicatorMetadata = IndicatorMetadata {
60    name: "HighPass",
61    description: "A second-order High Pass filter that rejects low-frequency components.",
62    usage: "Apply to price to isolate the cyclical component by attenuating the low-frequency trend. Use as the first stage before an oscillator or spectrum analyser.",
63    keywords: &["filter", "ehlers", "dsp", "high-pass", "cycle"],
64    ehlers_summary: "Ehlers derives the one-pole high-pass filter in Cycle Analytics for Traders analogously to EMA derivation, but applied to price differences rather than levels. It removes the DC component and low-frequency trend, leaving the cyclical content for downstream analysis.",
65    params: &[ParamDef {
66        name: "period",
67        default: "20",
68        description: "Critical period (wavelength)",
69    }],
70    formula_source: "https://github.com/lavs9/quantwave/blob/main/references/Ehlers%20Papers/implemented/UltimateSmoother.pdf",
71    formula_latex: r#"
72\[
73a_1 = \exp\left(-\frac{1.414\pi}{Period}\right)
74\]
75\[
76c_2 = 2a_1 \cos\left(\frac{1.414\pi}{Period}\right)
77\]
78\[
79c_3 = -a_1^2
80\]
81\[
82c_1 = (1 + c_2 - c_3) / 4
83\]
84\[
85HP = c_1 (Price - 2 Price_{t-1} + Price_{t-2}) + c_2 HP_{t-1} + c_3 HP_{t-2}
86\]
87"#,
88    gold_standard_file: "high_pass.json",
89    category: "Ehlers DSP",
90};
91
92#[cfg(test)]
93mod tests {
94    use super::*;
95    use crate::traits::Next;
96    use proptest::prelude::*;
97
98    #[test]
99    fn test_high_pass_basic() {
100        let mut hp = HighPass::new(20);
101        let inputs = vec![10.0, 11.0, 12.0, 13.0, 14.0, 15.0];
102        for input in inputs {
103            let res = hp.next(input);
104            println!("Input: {}, Output: {}", input, res);
105            assert!(!res.is_nan());
106        }
107    }
108
109    proptest! {
110        #[test]
111        fn test_high_pass_parity(
112            inputs in prop::collection::vec(1.0..100.0, 10..100),
113        ) {
114            let period = 20;
115            let mut hp = HighPass::new(period);
116            let streaming_results: Vec<f64> = inputs.iter().map(|&x| hp.next(x)).collect();
117
118            // Batch implementation
119            let mut batch_results = Vec::with_capacity(inputs.len());
120            let period_f = period as f64;
121            let a1 = (-1.414 * PI / period_f).exp();
122            let c2 = 2.0 * a1 * (1.414 * PI / period_f).cos();
123            let c3 = -a1 * a1;
124            let c1 = (1.0 + c2 - c3) / 4.0;
125
126            let mut hp_hist = [0.0; 2];
127            let mut price_hist = [0.0; 2];
128
129            for (i, &input) in inputs.iter().enumerate() {
130                let bar = i + 1;
131                let res = if bar < 4 {
132                    0.0
133                } else {
134                    c1 * (input - 2.0 * price_hist[0] + price_hist[1]) + c2 * hp_hist[0] + c3 * hp_hist[1]
135                };
136                hp_hist[1] = hp_hist[0];
137                hp_hist[0] = res;
138                price_hist[1] = price_hist[0];
139                price_hist[0] = input;
140                batch_results.push(res);
141            }
142
143            for (s, b) in streaming_results.iter().zip(batch_results.iter()) {
144                approx::assert_relative_eq!(s, b, epsilon = 1e-10);
145            }
146        }
147    }
148}
quantwave_core/indicators/high_pass.rs

quantwave_core/indicators/
high_pass.rs
